Monitoring of Hydroponics Plant and Prediction of Leaf Disease using IOT

Agriculture is the backbone of India, though it faces lots of challenges like little land property, excrements, pesticides, synthetic compounds utilized by rancher for horticulture and so on. In addition, Clients request for the quality food diet, liberated from horticultural synthetic compounds and pesticides. In this paper, a Hydroponics framework satisfying the above necessities is proposed to develop the plants naturally. This solution is feasible to a controlled climate such as, in any spot like room porch,overhang and so on. With this idea, a vast number of plants can be developed. This is one of the popular agribusinesses which can be more profitable whenever observed and controlled effectively. Hydroponics framework is a developing plant framework that does not utilize soil however utilizes water with supplements to save space. In this framework, we have utilized four transfer learning models for prediction, classification of disease and monitoring of the parameters. This data is fed to think speak cloud and the predictions are updated at regular intervals.The predicted parameters are temperature, soil pH, and the presence of disease. In our work, the VGG-19 model is adopted since it gives a good training and testing accuracy of 95.98% and 94.9% compared to other three training models.